code: def train(model_name, feature_name, saved_model_name):
      dir_names = [
          path.split("/")[2] for path in glob(f"{dataset_path}/*")
      ]
  
      model, accuracy = run_experiment(
          model_name, feature_name, dir_names
      )
  
      filename = f"trained_models/{saved_model_name}.sav"
      pickle.dump(model, open(filename, "wb"))
  
file_path: Mozart/src/train.py
imports: import cv2
  import random
  import imutils
  from glob import glob
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.neural_network import MLPClassifier
  from sklearn import svm
  import numpy
  import matplotlib.pyplot
  import pickle
label_desc: Use image node_id 8 for calling a global function with example usage: train(model_name, feature_name, saved_model_name) without return types